Clustering autism: using neuroanatomical differences in 26 mouse models to gain insight into the heterogeneity (original) (raw)

References

1. Abrahams BS, Geschwind DH . Connecting genes to brain in the autism spectrum disorders. Arch Neurol 2010; 67: 395–399.
   Article Google Scholar
2. Geschwind DH . Genetics of autism spectrum disorders. Trends Cogn Sci (Regul Ed) 2011; 15: 409–416.
   Article Google Scholar
3. Lord C, Risi S, DiLavore PS, Shulman C, Thurm A, Pickles A . Autism from 2 to 9 years of age. Arch Gen Psychiatry 2006; 63: 694–701.
   Article Google Scholar
4. Huerta M, Lord C . Diagnostic evaluation of autism spectrum disorders. Pediatr Clin North Am 2012; 59: 103–11–xi.
   Article Google Scholar
5. Amaral DG . The promise and the pitfalls of autism research: an introductory note for new autism researchers. Brain Res 2011; 1380: 3–9.
   Article CAS Google Scholar
6. Canitano R . Novel treatments in autism spectrum disorders: from synaptic dysfunction to experimental therapeutics. Behav Brain Res2012; 251: 125–132.
   Article Google Scholar
7. Veenstra-VanderWeele J, Blakely RD . Networking in autism: leveraging genetic, biomarker and model system findings in the search for new treatments. Neuropsychopharmacology 2012; 37: 196–212.
   Article CAS Google Scholar
8. Stessman HA, Bernier R, Eichler EE . A genotype-first approach to defining the subtypes of a complex disease. Cell 2014; 156: 872–877.
   Article CAS Google Scholar
9. Hrdlicka M, Dudova I, Beranova I, Lisy J, Belsan T, Neuwirth J et al. Subtypes of autism by cluster analysis based on structural MRI data. Eur Child Adolesc Psychiatry 2005; 14: 138–144.
   Article Google Scholar
10. Banerjee-Basu S, Packer A . SFARI gene: an evolving database for the autism research community. Dis Model Mech 2010; 3: 133–135.
    Article Google Scholar
11. Nakatani J, Tamada K, Hatanaka F, Ise S, Ohta H, Inoue K et al. Abnormal behavior in a chromosome-engineered mouse model for human 15q11-13 duplication seen in autism. Cell 2009; 137: 1235–1246.
    Article Google Scholar
12. Horev G, Ellegood J, Lerch JP, Son Y-EE, Muthuswamy L, Vogel H et al. Dosage-dependent phenotypes in models of 16p11.2 lesions found in autism. Proc Natl Acad Sci USA 2011; 108: 17076–17081.
    Article Google Scholar
13. Tabuchi K, Blundell J, Etherton MR, Hammer RE, Liu X, Powell CM et al. A neuroligin-3 mutation implicated in autism increases inhibitory synaptic transmission in mice. Science 2007; 318: 71–76.
    Article CAS Google Scholar
14. Moy SS, Nadler JJ, Young NB, Perez A, Holloway LP, Barbaro RP et al. Mouse behavioral tasks relevant to autism: phenotypes of 10 inbred strains. Behav Brain Res 2007; 176: 4–20.
    Article Google Scholar
15. International Mouse Knockout Consortium, International Mouse Knockout Consortium, Collins FS, International Mouse Knockout Consortium, Rossant J, International Mouse Knockout Consortium, Wurst W . A mouse for all reasons. Cell 2007; 128: 9–13.
    Article Google Scholar
16. Chadman KK, Gong S, Scattoni ML, Boltuck SE, Gandhy SU, Heintz N et al. Minimal aberrant behavioral phenotypes of neuroligin-3 R451C knockin mice. Autism Res 2008; 1: 147–158.
    Article Google Scholar
17. Etherton M, Földy C, Sharma M, Tabuchi K, Liu X, Shamloo M et al. Autism-linked neuroligin-3 R451C mutation differentially alters hippocampal and cortical synaptic function. Proc Natl Acad Sci USA 2011; 108: 13764–13769.
    Article CAS Google Scholar
18. Lerch JP, Gazdzinski L, Germann J, Sled JG, Henkelman RM, Nieman BJ . Wanted dead or alive? The tradeoff between in-vivo versus ex-vivo MR brain imaging in the mouse. Front Neuroinform 2012; 6: 6.
    Article Google Scholar
19. van Eede MC, Scholz J, Chakravarty MM, Henkelman RM, Lerch JP . Mapping registration sensitivity in MR mouse brain images. Neuroimage 2013; 82: 226–236.
    Article Google Scholar
20. Bock NA, Konyer NB, Henkelman RM . Multiple-mouse MRI. Magn Reson Med 2003; 49: 158–167.
    Article Google Scholar
21. Lerch JP, Sled JG, Henkelman RM . MRI phenotyping of genetically altered mice. Methods Mol Biol 2011; 711: 349–361.
    Article CAS Google Scholar
22. Ellegood J, Babineau BA, Henkelman RM, Lerch JP, Crawley JN . Neuroanatomical analysis of the BTBR mouse model of autism using magnetic resonance imaging and diffusion tensor imaging. Neuroimage 2013; 70: 288–300.
    Article Google Scholar
23. Nieman BJ, Lerch JP, Bock NA, Chen XJ, Sled JG, Henkelman RM . Mouse behavioral mutants have neuroimaging abnormalities. Hum Brain Mapp 2007; 28: 567–575.
    Article Google Scholar
24. Lerch JP, Yiu AP, Martinez-Canabal A, Pekar T, Bohbot VD, Frankland PW et al. Maze training in mice induces MRI-detectable brain shape changes specific to the type of learning. Neuroimage 2011; 54: 2086–2095.
    Article Google Scholar
25. Brodkin ES . BALB/c mice: low sociability and other phenotypes that may be relevant to autism. Behav Brain Res 2007; 176: 53–65.
    Article CAS Google Scholar
26. McFarlane HG, Kusek GK, Yang M, Phoenix JL, Bolivar VJ, Crawley JN . Autism-like behavioral phenotypes in BTBR T+tf/J mice. Genes Brain Behav 2008; 7: 152–163.
    Article CAS Google Scholar
27. Cahill LS, Laliberté CL, Ellegood J, Spring S, Gleave JA, Eede MCV et al. Preparation of fixed mouse brains for MRI. Neuroimage 2012; 60: 933–939.
    Article Google Scholar
28. Spring S, Lerch JP, Henkelman RM . Sexual dimorphism revealed in the structure of the mouse brain using three-dimensional magnetic resonance imaging. Neuroimage 2007; 35: 1424–1433.
    Article Google Scholar
29. Nieman BJ, Flenniken AM, Adamson SL, Henkelman RM, Sled JG . Anatomical phenotyping in the brain and skull of a mutant mouse by magnetic resonance imaging and computed tomography. Physiol Genomics 2006; 24: 154–162.
    Article CAS Google Scholar
30. Nieman BJ, Bock NA, Bishop J, Chen XJ, Sled JG, Rossant J et al. Magnetic resonance imaging for detection and analysis of mouse phenotypes. NMR Biomed 2005; 18: 447–468.
    Article Google Scholar
31. Collins DL, Neelin P, Peters TM, Evans AC . Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr 1994; 18: 192–205.
    Article CAS Google Scholar
32. Avants BB, Yushkevich P, Pluta J, Minkoff D, Korczykowski M, Detre J et al. The optimal template effect in hippocampus studies of diseased populations. Neuroimage 2010; 49: 2457–2466.
    Article Google Scholar
33. Dorr AE, Lerch JP, Spring S, Kabani N, Henkelman RM . High resolution three-dimensional brain atlas using an average magnetic resonance image of 40 adult C57Bl/6 J mice. Neuroimage 2008; 42: 60–69.
    Article CAS Google Scholar
34. Suzuki R, Shimodaira H . Pvclust: an R package for assessing the uncertainty in hierarchical clustering. Bioinformatics 2006; 22: 1540–1542.
    Article CAS Google Scholar
35. Courchesne E, Campbell K, Solso S . Brain growth across the life span in autism: age-specific changes in anatomical pathology. Brain Res 2011; 1380: 138–145.
    Article CAS Google Scholar
36. Raznahan A, Wallace GL, Antezana L, Greenstein D, Lenroot R, Thurm A et al. Compared to what? Early brain overgrowth in autism and the perils of population norms. Biol Psychiatry 2013; 74: 563–575.
    Article Google Scholar
37. Gleave JA, Wong MD, Dazai J, Altaf M, Henkelman RM, Lerch JP et al. Neuroanatomical phenotyping of the mouse brain with three-dimensional autofluorescence imaging. Physiol Genomics 2012; 44: 778–785.
    Article CAS Google Scholar
38. Toal F, Daly EM, Page L, Deeley Q, Hallahan B, Bloemen O et al. Clinical and anatomical heterogeneity in autistic spectrum disorder: a structural MRI study. Psychol Med 2010; 40: 1171–1181.
    Article CAS Google Scholar
39. Amaral DG, Schumann CM, Nordahl CW . Neuroanatomy of autism. Trends Neurosci 2008; 31: 137–145.
    Article CAS Google Scholar
40. Stanfield AC, McIntosh AM, Spencer MD, Philip R, Gaur S, Lawrie SM . Towards a neuroanatomy of autism: A systematic review and meta-analysis of structural magnetic resonance imaging studies. Eur Psychiatry 2008; 23: 289–299.
    Article Google Scholar
41. Kurth F, Narr KL, Woods RP, O'Neill J, Alger JR, Caplan R et al. Diminished gray matter within the hypothalamus in autism disorder: a potential link to hormonal effects? Biol Psychiatry 2011; 70: 278–282.
    Article Google Scholar
42. Fatemi SH, Aldinger KA, Ashwood P, Bauman ML, Blaha CD, Blatt GJ et al. Consensus paper: pathological role of the cerebellum in autism. Cerebellum 2012; 11: 777–807.
    Article Google Scholar
43. Kana RK, Libero LE, Moore MS . Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders. Phys Life Rev 2011; 8: 410–437.
    Article Google Scholar
44. Ey E, Leblond CS, Bourgeron T . Behavioral profiles of mouse models for autism spectrum disorders. Autism Res 2011; 4: 5–16.
    Article Google Scholar
45. Bailey KR, Rustay NR, Crawley JN . Behavioral phenotyping of transgenic and knockout mice: practical concerns and potential pitfalls. ILAR J 2006; 47: 124–131.
    Article CAS Google Scholar
46. Radyushkin K, Hammerschmidt K, Boretius S, Varoqueaux F, El-Kordi A, Ronnenberg A et al. Neuroligin-3-deficient mice: model of a monogenic heritable form of autism with an olfactory deficit. Genes Brain Behav 2009; 8: 416–425.
    Article CAS Google Scholar
47. Saywell V, Viola A, Confort-Gouny S, Le Fur Y, Villard L, Cozzone PJ . Brain magnetic resonance study of Mecp2 deletion effects on anatomy and metabolism. Biochem Biophys Res Commun 2006; 340: 776–783.
    Article CAS Google Scholar
48. Ward BC, Agarwal S, Wang K, Berger-Sweeney J, Kolodny NH . Longitudinal brain MRI study in a mouse model of Rett Syndrome and the effects of choline. Neurobiol Dis 2008; 31: 110–119.
    Article CAS Google Scholar
49. Dodero L, Damiano M, Galbusera A, Bifone A, Tsaftsaris SA, Scattoni ML et al. Neuroimaging evidence of major morpho-anatomical and functional abnormalities in the BTBR T+TF/J mouse model of autism. PLoS ONE 2013; 8: e76655.
    Article CAS Google Scholar
50. Portmann T, Yang M, Mao R, Panagiotakos G, Ellegood J, Dolen G et al. Behavioral abnormalities and circuit defects in the basal ganglia of a mouse model of 16p11.2 deletion syndrome. Cell Rep 2014; 7: 1077–1092.
    Article CAS Google Scholar
51. Michalon A, Sidorov M, Ballard TM, Ozmen L, Spooren W, Wettstein JG et al. Chronic pharmacological mGlu5 inhibition corrects fragile X in adult mice. Neuron 2012; 74: 49–56.
    Article CAS Google Scholar

Download references